The virtual worlds where robots are trained

This video can not be played Freddo the robot in action at Vsim Freddo the robot walks across the office and takes a plastic bottled offered by a staff member. Given that a robot recently beat Usain Bolt's 100m sprint record, it's not the most startling achievement. But the speed , recognise the bottle and grasp it is impressive. It took just a few minutes to develop those skills and upload them to Freddo. His developers say rival systems could take days to attain such skills. I'm at Vsim, a British start-up based in Cambridge. Founders Michelle Lu and Kier Storey hope one day their software will control robots that can navigate and do useful tasks in the home and workplace. But there's a long way to go. "It's a weird situation with robotics because actually the stuff that we find as humans to be incredibly difficult, like gymnastics, you can get robots to do reasonably well. The stuff that humans are really good at, like fine dexterity, is really hard in robots," Storey says. Vsim founders Michelle Lu and Kier Storey Freddo's skills were honed in a virtual environment, where a task can be performed in a computer simulation millions of times. Once the optimum solution (known as a policy) is found, it can be uploaded and used - in this case Freddo. Such virtual simulations are a common way to train robots. Tech giant Nvidia has a system called Isaac Sim which works that way - Lu and Storey both worked on an early version of it. In 2022 they decided to set up Vsim, to build the their own training system environment and other tools. As they were starting from scratch Lu and Storey could optimise the software to exploit the powerful computer chips used in AI, known as graphics processing units or GPUs. "The underlying algorithms that we were using for most of these robotic simulations they hark back to the 1970s and 1980s, but those algorithms are not really brilliant fits for GPUs," Storey says. Within months they realised their system could work much faster than anything they had seen before. "Eighteen months in and we actually have a completely functional, super high-performance simulator," says Lu. The software is so efficient that it can run on the hardware carried by Freddo. That means the robot can run tens of thousand of simulations while it is moving around. "It can look about a second, or so, ahead into the future for 20,000 different kind of combinations of things that might happen," Storey explains.